基于最小约简的粗糙集数据挖掘算法研究

Research on Data Mining Algorithms Based on Reduction Rough Sets

为了进一步提高粗糙集模式数据挖掘算法的效率,论文提出一种基于约简粗糙集的数据挖掘算法。具体研究过程为:首先提出一种优化的启发式约简算法,并分析制定了启发式规则,接着研究约简粗糙集的实现过程,最后采用对比实验来验证约简粗糙集模式数据挖掘算法的可行性。研究结果表明:论文所提算法的运行效率高出其他主流算法近30%,为高效的数据挖掘奠定了理论基础。

In order to further improve the efficiency of rough set pattern data mining algorithm,it proposes a data mining algo⁃rithm based on reduced rough set in this paper.The specific research process is as follows.First,an optimized heuristic reduction al⁃gorithm is proposed,and the heuristic rules are analyzed and formulated.Then,the implementation process of reduced rough set is studied.Finally,the feasibility of reduced rough set pattern data mining algorithm is verified by comparative experiments.The re⁃sults show that the efficiency of the proposed algorithm is nearly 30%higher than that of other mainstream algorithms,which lays a theoretical foundation for efficient data mining.